As an integral part of production planning control, order release management is critical to enhance the competitiveness and production efficiency of companies. Previous literature shows limited application of optimization-based models in assembly job shops, primarily due to the intricate nature of product structures and assembly operations. Therefore, based on the idea of the allocated clearing function (ACF) model, we introduce material flow constraints and complex assembly structure constraints during the assembly stage, proposing the assembly job shop allocated clearing function (AACF) model. The performance of the AACF model and the rule-based mechanisms in terms of cost and timing measures are compared through experiments containing 6 factors and 96 scenarios. The results show that the AACF model performs better in terms of cost management, service level and order due date deviation. In addition, a sensitivity analysis of the objective function parameters is performed to confirm the robustness of the AACF model. Finally, a case application in a real assembly shop illustrates the feasibility and validity of the proposed AACF model.

Workload control theory seeks to align capacity and demand to improve delivery performance. However, workload control researchers mainly focused on input control, which regulates the input of work to the production system, thereby neglecting output control, which uses capacity adjustments to regulate the outflow of the work. Moreover, few existing studies on output control investigate a temporarily increase in capacity. This paper introduces a new search direction for output control which does not require an increase in capacity – labour flexibility. Idle operators can move from their workstation to another, thus temporarily increasing the output of that workstation without extra capacity. Using simulation of a five workstations flow shop line, we highlight the positive performance effect of labour flexibility. However, this comes at the cost of high labour movement. Introducing a load-based constraint on when workers are allowed to significantly reduces labour movement, while realizing most of the performance improvement observed for unconstrained labour movement. This has important implications for future research and practice.

The research discusses in this paper concerns the improvement allocation policies to reduce the process time in job-shop manufacturing systems. The policies proposed are based on the evaluation of the workload control of the entire manufacturing system. Three policies are proposed: centralized, distributed and proportional. A simulation model is used to test the proposed policies under different conditions as: static and dynamic demand; introduction of machine breakdowns; different level of average manufacturing system utilization. The performance measures are compared to a manufacturing system without policies. The simulation results show that the improvement allocation allows to improve the performance with limited investment (average reduction of process time needed) and how the machine breakdowns and demand changes lead to different better policy. The decision maker can use these results to decide the better policy to use.